Information Retrieval Based Nearest Neighbor Classification for Fine-Grained Bug Severity Prediction
Bugs are prevalent in software systems. Some bugs are critical and need to be fixed right away, whereas others are minor and their fixes could be postponed until resources are available. In this work, we propose a new approach leveraging information retrieval, in particular BM25-based document simil...
Saved in:
Main Authors: | TIAN, Yuan, LO, David, SUN, Chengnian |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2012
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/1586 https://ink.library.smu.edu.sg/context/sis_research/article/2585/viewcontent/IR_NNC_severity_av.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
On the unreliability of bug severity data
by: TIAN, Yuan, et al.
Published: (2015) -
DRONE: Predicting Priority of Reported Bugs by Multi-factor Analysis
by: TIAN, Yuan, et al.
Published: (2013) -
Towards More Accurate Retrieval of Duplicate Bug Reports
by: SUN, Chengnian, et al.
Published: (2011) -
Improved Duplicate Bug Report Identification
by: TIAN, Yuan, et al.
Published: (2012) -
Automated Prediction of Bug Report Priority Using Multi-Factor Analysis
by: TIAN, Yuan, et al.
Published: (2015)